Remaining useful life prognostic estimation for aircraft subsystems or components: A review

Abstract

The techniques of remaining useful life (RUL) estimation are playing a more and more important role in aircraft safety and condition based maintenance. This paper gives an overview of RUL prognostic estimation approaches applied to aircraft subsystems or components. Existing RUL estimation approaches are categorized into three types, namely model-based approaches, data-driven approaches and fusion approaches and their characteristics are comprehensively introduced. Moreover, three common and promising methods: particle filtering, neural network and relevant vector machine as well as their advantages and disadvantages are discussed in details. Finally, the future challenges concerned with RUL prediction are also presented.